Abstract
Reporters obtained the following quote from the background information supplied by the inventors: “Machine learning generative models can be implemented in a va riety of applications such as imageto- text generation, style transfer, image-to -image translation, and text-to-three-dimensional (3D) object generation. Recent studies on text-to-image generation have shown that large generative models, af ter being pre-trained on large datasets, are able to generate photorealistic con tents that are highly matched with given text prompts. One subclass of these gen erative models includes diffusion models that are capable of achieving more dive rsified generated content.”
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